Phi Beta Iota: This article, written in 2007, remains the standard in the field for both brevity and authoritativeness.
Business Intelligence is data mining, not intelligence. Competitive Intelligence focuses on competitors and does not do 360 degree holistic analytics.
The modern term for a full service program is Commercial Intelligence, which uses only open sources and ethical methods. It should not be confused with secret government intelligence or with illegal industrial espionage.
Mr. Herring is also the creator of the now globally-recognized “Herring Triangle” graphic of four levels of commercial intelligence and their relative costs.
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How Much Is Your Competitive Intelligence Worth?
By Jan P. Herring, Herring & Associates LLC
Society of Competitive Intelligence Professionals (SCIP)
Volume 10 • Number 2 • March-April 2007
Intelligence professionals are often asked to assess the value of their business intelligence (BI) or competitive intelligence (CI) effort. Most professionals say it cannot be done. I disagree! You can measure its value both quantitatively and, just as important, qualitatively—in other words, how it is perceived by those who use it. Let’s discuss these two objectives and some ways to approach the task.
EFFECTIVENESS AND VALUE
I first addressed the problem of assessing intelligence’s value in a research report, Measuring the Effectiveness of Competitive Intelligence, which I produced for SCIP in 1996. Our objective was to find some quantifiable means of evaluating competitive intelligence. In that report, I researched the following three related areas:
• Competitive intelligence itself
• Several related corporate functions, such as library services, market research, and strategic planning
• Executives from companies with competitive intelligence programs to determine how they evaluated the intelligence they received.
Although none of the research activities revealed any useful quantitative measures, the search did uncover a serendipitous set of “measures of effectiveness” (MOEs) that had been developed and used by professionals in the commercial information technology fields, or as it was then called, office automation (OA).
Like CI professionals, office automation managers recognized that they had to directly involve their clients in measuring the value of their OA services. Whereas OA focused on processing and delivering internal information to its users, CI focuses on acquiring, processing, and delivering external information to management. The resulting MOEs seemed quite compatible; only the information content differed.
A key part of the measures-of-effectiveness process for office automation identified management’s expected results before the actual measurement process begins. This was analogous to CI’s Key Intelligence Process (KIT). Subsequently, this process accounted for the time and/or money spent, saved, or made in the business activity involved.
The OA process then called for the producer and user to jointly assess the resulting value of the business activity involved, and communicate the results to management.
EFFECTIVENESS MEASURES IN CONTEXT
To ensure that the OA measures of effectiveness (see table 1) were both applicable and practical for competitive intelligence practitioners, I examined each in the context of some intelligence experiences that I had either with my clients or when I was managing the intelligence program at Motorola. Here’s an example for Time Savings: a competitive assessment, developed through the coordinated effort of business units with a common competitor, not only produced more comprehensive and insightful results, but also was completed in a shorter time.
Table 1. MEASURES OF EFFECTIVENESS USED BY OFFICE AUTOMATION
Savings for both professional and support personnel.
Elimination or reduction in expenses.
Elimination of planned expenses.
Increases in the number of sales or size of sales.
Benefits that are not easily related to specific dollar values, such as more effective strategies or better new products and services.
By gathering scientific and technological (S&T) intelligence to identify a proven research and development (R&D) process, CI demonstrated its Cost Savings MOE. This intelligence prompted the client company to not explore all the various alternatives but rather to concentrate its R&D resources on a proven process.
An excellent real-world example of the Cost Avoidance MOE involves a major pharmaceutical firm that planned an expenditure of research funds but did not spend the money; the competitive intelligence department provided evidence that its planned new product was at least two years behind the competition. And companies can measure Revenue Increases in any number of ways, including an increased number of new sales or the size of a new contract that resulted from the application of good market intelligence. In the final analysis, I was convinced that the OA measures of effectiveness could also work in the competitive intelligence field.
SENIOR EXECUTIVE INTERVIEWS
In that 1996 SCIP research project, I also interviewed some 20 senior executives who represented eight major companies in very different types of businesses. The businesses included aerospace, electronics, and financial services.
Surprisingly, none of the executives were interested in quantitative measures for their intelligence programs. In fact, the chief financial officer of the financial services firm did not mention financial measurement of any kind during the formal interview. When questioned about its absence, he replied, “We want to see our BI cause the business to take action—we can always go back and measure its financial value later!” All the interviewed executives stated that they expected to see the intelligence have some “visible” impact on the company or its management decisions.
A PROJECT’S VALUE
In my experience, measures of effectiveness (MOEs) can best be applied to specific intelligence projects. But you should select the particular measure before the project is actually begun—it is difficult to go back and recover project specific data after the project is complete. I suggest initially selecting several MOEs to be certain the expected result is amenable to the type of measurement you chose.
A brief example may be helpful. The management of a high-tech manufacturing firm determined they needed to diversify their product base but still leverage their technological competence. They would use their existing biotech production process but produce an entirely different type of end product. To do this as quickly as possible they decided to purchase the end-product technology for $2.5 million from another firm and use it in their own production processes and facility.
However, because the new product would compete in an entirely different market, the senior managers needed both marketing support and competitive intelligence for the new product’s intended marketplace. They would hire an appropriate market research firm to assess the potential markets, but decided to form an ad hoc competitive intelligence team made up of four to five current employees, who would work part-time on the project.
The ad hoc team performed all the usual competitive intelligence operations. In doing so, the team identified a technical conference where the new $2.5 million end-product technology would be featured. This provided an excellent opportunity to look at both competing product technologies and the competitor companies that the firm would face in the new marketplace.
The team prepared well for the conference, including both business and technical personnel in the trade show collection effort. The information they collected on the new competitors was impressive. They not only learned who the competitors were but also discovered many of the competitive tactics used in that marketplace. But the real surprise came from the scientific & technological intelligence (S&T) they acquired. The firm that was selling the new-product technology gave a public presentation, intending to increase its sales, but during that presentation they divulged a great deal of the technology’s specific composition—probably more than they had intended.
When the competitive intelligence team returned from the conference, they met with their own scientists and patent attorneys. They concluded that the technology, which the firm had intended to purchase for $2.5 million, had been publicly revealed. The firm would not have to spend that money!
From the beginning, the competitive intelligence team had intended to show the project’s cost benefit. The team tracked all the cost data, but was not sure what type of performance measure it could use. A simple return on investment (ROI) was the most likely measure. As it turned out, the $2.5 million not spent fell into the category of Cost Avoidance (planned expenditures not spent), an easily recognizable MOE. But because they had kept accurate records on the team’s expenses (about $175,000), they were also able to calculate the project’s return on investment: $2.5 million minus costs ($175,000) divided by cost ($175,000) resulted in a simple ROI of over 1,300 percent. Either measure was more than acceptable to the company’s management team.
THE CI PROGRAM’S VALUE
Determining value for competitive intelligence programs as a whole is somewhat more difficult. With some effort on the part of all involved, the results can be very satisfying. For example, during the early 1990s, NutraSweet CEO Bob Flynn estimated that the company’s intelligence program was worth a least $50 million a year over a five-year period. The evaluation process was a joint effort between the business intelligence and finance departments. The BI department identified the business decisions and major projects to which they had contributed over the five-year period, and the finance department assessed the dollar value for each decision and project. (Not all defined intelligence contributions were accepted.)
The final sum, a combination of money saved or made, was an average of $50 million per year. When Bob reported this finding at the 1994 SCIP Annual Conference in Boston, he considered it a very conservative estimate. For a program that cost about a million dollars a year, BI produced a pretty good ROI (although management was quite satisfied with the dollar amount alone).
Bob explained that the intelligence program was a major contributor to the company’s competitive advantage in marketing, manufacturing, organizational structure, and financial activities. Competitive intelligence had helped them make more good decisions and fewer bad ones.
In the final analysis, business and competitive intelligence programs perceived as “making money” for the company are successful. They achieve that recognition or awareness by helping management and the program’s other clients successfully perform their jobs, including the following tasks:
• Better business decisions
• More effective strategic plans and competitive strategies
• More successful products and services
• Increased sales and marketplace success.
Good intelligence also minimizes the risk that the company and its management will be surprised by competitors or marketplace events that could upset the company’s business plans or new product introductions. Furthermore, in today’s global business world, good intelligence (including counterintelligence) protects the company’s intellectual property from competitors who attempt to obtain it.
The Competitive Intelligence Foundation’s 2005 Survey, State of the Art: Competitive Intelligence, found that today more organizations are assessing the effectiveness and value of their intelligence activities. Some 70 percent said they measured its effectiveness in some way and 65 percent are trying to assess its value. However, 40 percent of those contributing to the survey said they had no formal process for assessing their competitive intelligence effectiveness or value.
Table 2 shows the Foundation’s Survey results.
Table 2. MEASURES OF EFFECTIVENESS AND VALUE
Assessing CI’s Effectiveness
Customer satisfaction 58%
Decisions made/supported 48%
Actions taken 43%
Strategies enhanced 38%
New products/services 22%
Assessing CI’s Value
New/increased revenue 29%
Cost savings or avoidance 27%
Time savings 22%
Financial goals met 20%
ROI calculations 14%
[Source: State of the Art: Competitive Intelligence Competitive Intelligence Foundation, 2006, Alexandria VA]
Although the survey did not address just how intelligence practitioners are attempting to measure effectiveness, the types of business activities being assessed are interesting. Most lend themselves to rather straightforward qualitative or direct interview techniques, Customer Satisfaction being the most popular. However, I must point out that the senior executives interviewed in the earlier SCIP project did not favor this technique—they wanted to see some actual business benefit from the intelligence activities, such as increased sales or profits, greater market share, or a successful company acquisition.
The other effectiveness topics being addressed indicates to me that the companies involved focused their competitive intelligence operations on some of the most important business activities confronting their managers, such as decision making, strategies, and new products and services development. I suspect that if their competitive intelligence professionals attempted to measure some of their intelligence activities, those measurements also would have been successful.
The lesser use of value-related measures, such as those advocated by the office automation community (Cost Savings, Time Savings, and Revenue Increases) probably reflect the difficulty of obtaining clear-cut financial data and related agreements from other business contributors.
Nevertheless, the Foundation’s Survey data indicates that the competitive intelligence community has made substantial progress in assessing CI’s value since SCIP began advocating the practice in 1996!
CI SUCCESS AS A PART OF CORPORATE CULTURE
In the final analysis, the best measure of a competitive intelligence program’s value comes in the form of “success stories” told by those who benefited from the intelligence. For example:
• Proctor & Gamble’s competitive benchmarking of a competitor’s distribution system saved it some $40 million when they applied the lessons learned.
• Motorola’s successful acquisition of a European firm, credited to its business intelligence department, increased its yearly European profits by some $10 million—a good example of revenue enhancement.
• NutraSweet’s CEO commented that one decision—not to react to a competitor’s perceived initiative—actually saved the company $38 million. (A classic example of the cost-saving MOE.)
• General Motors’ competitive benchmarking program was credited with saving the company hundreds of millions in comparable manufacturing costs.
• Merck’s CI program was judged to be worth over $100 million in retained sales for one product alone.
The reporting of such success stories by a company’s management is not simply good for the competitive intelligence program’s success. It also adds to the shared belief that competitive intelligence is a good thing for the company—making it a part of the organization’s corporate culture.
YOU CAN EVALUATE
In the final analysis, you can evaluate your company’s competitive intelligence effort—if you properly define what you intend to measure and how you intend to measure it. In my experience, senior-level users of intelligence are not as interested in financial or quantitative measures of your products and services as they are in having intelligence that visibly affects their decision making or business actions in a positive fashion. They do, however, expect to see some form of related action. Actions that lead to greater sales, profits, or other measures of business success are the most valued.
An old friend and associate, Robert Steele, probably put it best: “Information costs money … Intelligence makes money!” Essentially, any competitive information that a business manager acts on becomes intelligence. And intelligence that makes money for a company is valued intelligence!
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Jan P. Herring is a well-recognized expert in the field of Business Intelligence and a frequent speaker at SCIP functions. In addition he is a founding member, SCIP Fellow, and 1993 recipient of the society’s highest award, the Meritorious Award, for his contribution to both SCIP and the profession. Mr. Herring is also the first recipient of the Faye Brill Service Award for his many years of direct and extraordinary support for SCIP. Jan’s professional experience includes developing and managing Motorola’s highly acclaimed intelligence program, cofounding the Academy of Competitive Intelligence, and in his earlier career, setting up the U.S. government’s first business intelligence program. Upon leaving the government, where Mr. Herring had served as a professional intelligence officer at the CIA, he was awarded the Agency’s highest honor, the Medal of Distinction. He now has his own consulting firm, Herring & Associates, which helps intelligence professionals set up and manage their own Business Intelligence programs, as well as improve their existing intelligence processes. Jan can be reached at jpherring **at** snet.net.